Method for detecting and compensating for defective printing nozzles in an ink jet printing machine

ABSTRACT

A method for detecting and compensating for defective printing nozzles in an ink jet printing machine by using a computer includes printing printing nozzle test charts next to an actual print in a production run, subsequently recording and digitizing the printed printing nozzle test charts by using at least one image sensor, evaluating recorded test charts and, based thereon, defining characteristic values for all printing nozzles contributing to the printed printing nozzle test charts by using the computer, calculating a failure probability for every contributing printing nozzle based on the determined characteristic values by applying a statistical prediction model using the computer, and switching off and compensating for all printing nozzles exceeding a first defined threshold for the calculated failure probability. A printing operation is then carried out on the ink jet printing machine with printing nozzle compensation.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority, under 35 U.S.C. § 119, of GermanPatent Application DE 10 2017 221 035.4, filed Nov. 24, 2017; the priorapplication is herewith incorporated by reference in its entirety.

BACKGROUND OF THE INVENTION Field of the Invention

The invention relates to a method for detecting and compensating fordefective printing nozzles in an ink jet printing machine in whichdefective printing nozzles are predicted by using a prediction model.

The technical field of the invention is the field of digital printing.

The quality which an ink jet printing machine, in particular anindustrial large-format ink jet printing machine, can deliver alwaysdepends on the performance of the individual printing nozzles of the inkjet print heads that are used. The performance of individual printingnozzles may deteriorate until the nozzle fails completely. Such afailure may be caused by foreign bodies such as dust particles enteringthe nozzle or by dried-on ink residues that clog the nozzle inparticular if the ink jet print heads have not been used for a longerperiod of time. Both causes of defects result in partial or total nozzleopening blockages, which make the affected printing nozzles unable tojet the intended amount of ink in the form of jetted ink droplets. Inaddition, if the printing nozzle is partly clogged or blocked, the dotit prints may be offset from the intended position, i.e. the nozzle mayjet at an angle. Such a nozzle performance glitch results in artifactsin the print that they create, for instance in white lines in the caseof a failed nozzle or, in the case of printing nozzles that jet at anangle, in white lines where the print dot of the nozzle in questionshould have been and a black line where the printing nozzle that jets atan angle misplaces ink and thus contributes to an undesired applicationof too much ink at that location. Such defective printing nozzles thatcreate image artifacts in the form of white lines and black lines aresummarily referred to as missing nozzles.

In order to be able to continue to use an affected ink jet print head inwhich such missing nozzles occur and to avoid having to resort to thecostly measure of changing the ink jet print heads whenever individualmissing nozzles occur, several compensation processes for missingnozzles have become known in the art. Among other approaches, suchcompensation strategies include the provision of redundant printingnozzles and print heads for the same printing color and, in the case ofmulticolor prints, the replacement of missing nozzles by printingnozzles that print different printing colors at the location of themissing nozzle in the printed image. When defective printing nozzleshave been identified, another approach is to adapt the print prior tothe screening process in such a way as to minimize the number ofartifacts that the missing nozzles will later create in the print. Theadaptions may include adapting gray values in the digital print image inthe region that the missing nozzles will produce after the screeningprocess and offsetting entire image objects in the digital print forimposition.

The most common approach when defective printing nozzles have beenidentified is, however, to adapt the screened print in such a way thatthe ink jet printing machine is actuated in a way for printing nozzlesnext to the missing nozzle to jet more ink to compensate for thedefective printing nozzle.

However, to be able to compensate for defective printing nozzles, theyneed to be detected first. Again, a variety of detection methods havebecome known in the art. They may be broadly divided into two differentapproaches. The first approach is to provide an image recording systemwith at least one image sensor for continuously scanning the printedimage, to digitize the printed image, to feed the data to a computerthat evaluates the digitized images and examines them to find potentialmissing nozzles. The computer will then forward the results of theevaluation to where measures are taken to compensate for the missingnozzles that have occurred. A disadvantage of that approach is that inan evaluation of the images that are currently printed in a productionrun on the printing machine, defective printing nozzles may frequentlynot be detected because they may not contribute to the current print,for instance. In addition, the print data to be produced in the actualprint are rarely suitable for detecting defective printing nozzles in anoptimum way.

Another approach to detecting defective printing nozzles is thus toprint printing nozzle test charts that have been specifically optimizedfor detecting defective printing nozzles. Those test charts are printedonto the printing substrate in addition to the actual print that is tobe created and are subsequently evaluated by the aforementioned imagerecording system. A disadvantage of that method is that it requiresadditional image data to be created on the substrate, slightlyincreasing the performance and workload of the ink jet printing machine.Another aspect to be considered is that the detection charts require acertain amount of space on a print sheet or in a label section and needto be printed individually for every color.

In general, when printing nozzle test charts are printed, every printingnozzle prints small image objects such as short vertical lines that willthen be examined in the course of a detection process carried out by theevaluation computer of the image recording system. The characteristicsof an image object that has been created by an individual nozzle thenallows conclusions to be drawn about the performance of the nozzle inquestion. The evaluation relies on thresholds that define how long anozzle is considered to be functioning and from which point it is to beconsidered defective. Depending on those thresholds, a decision is madewhether to switch a printing nozzle off or on again. The quality ofevery individual nozzle needs to be known for the comparison. It isdescribed by specific characteristic values such as the clarity, slope,or gray value of the vertical line printed by the respective printingnozzle. The characteristic values are determined at defined intervals onthe fly, i.e. during an ongoing printing operation. In accordance withthe prior art, the characteristic values are categorized on the basis ofempirical values. Printing nozzles having values which exceed a specificthreshold are switched off. They may be switched on again when a certainnumber of successive detections, for instance 5, provide results belowthe threshold. The methods that are currently known do not provide anyforecast or prediction of nozzle quality. However, a printing nozzle isonly switched off when the quality threshold is reached or exceeded. Asa consequence, a threshold that is too tolerant will result in theproduction of waste, and a threshold that is too sensitive will resultin a premature switching off of printing nozzles, which in turn resultsin unnecessary compensation. Both phenomena have a negative impact onthe quality and/or performance of the ink jet printing machine.

SUMMARY OF THE INVENTION

It is accordingly an object of the invention to provide a method fordetecting and compensating for defective printing nozzles in an ink jetprinting machine, which overcomes the hereinafore-mentioneddisadvantages of the heretofore-known methods of this general type andwhich provides a more efficient and more effective method forcontrolling the quality of an ink jet printing machine by monitoring theperformance of the printing nozzles.

With the foregoing and other objects in view there is provided, inaccordance with the invention, a method for detecting and compensatingfor defective printing nozzles in an ink jet printing machine by using acomputer, the method comprising the steps of printing printing nozzletest charts next to the actual print in the production run, subsequentlyrecording and digitizing the printed printing nozzle test charts byusing at least one image sensor, evaluating the recorded test charts,and, based thereon, defining characteristic values for all printingnozzles that contribute to the printing of the printing nozzle testcharts by using the computer, calculating a failure probability forevery contributing printing nozzle based on the determinedcharacteristic values by applying a statistic prediction model by usingthe computer, switching off and compensating for all printing nozzlesthat exceed a first defined threshold for the calculated failureprobability, and carrying out a printing operation on the ink jetprinting machine with printing nozzle compensation.

A key element of the method of the invention is that not only does itmonitor the print for printing nozzle failures, but it also checks theentire state of all printing nozzles that contribute to the print toassess their performance. The current state of the printing nozzles isdefined on the basis of characteristic values that are directly derivedfrom the printed printing nozzle test chart including individual imageobjects for every individual printing nozzle. Based on this currentstate of the individual printing nozzles, a statistic prediction modelis used to calculate the failure probability of every single printingnozzle. If the calculated failure probability of a printing nozzleexceeds a specified threshold, the printing nozzle is deactivated. Ofcourse, the deactivated printing nozzle will then create a white line inthe actual print, which means that it needs to be compensated for in asuitable way. The reason for switching off printing nozzles that havebeen found defective even though they may not have failed completely andmay still be partly functional or jet at an angle is that a definedstarting condition is needed for compensation purposes. This definedstarting condition may be created by switching off nozzles that do nolonger perform correctly. If this was not done and a printing nozzlethat prints to a reduced extent was allowed to continue to print despitecompensation measures, a dedicated compensatory approach adapted to thespecific defect characteristics would have to be found for every singleprinting nozzle that prints with a defect. That would make thecompensation process much more complicated. Thus, nozzles that aredefective in this way are intentionally switched off. However, in themethod of the invention, the key parameter to decide whether a printingnozzle is to be switched off is not the actual current condition of theprinting nozzle, but the individual nozzle's failure probability thathas been calculated in accordance with the invention. If it exceeds thethreshold, the nozzle is switched off. If it does not exceed thethreshold, the nozzle may be allowed to go on printing. An advantage ofthis approach is that printing nozzles that are highly likely to failsoon will be proactively treated and compensated for. In contrast to theprior art, the method of the invention does not wait until a printingnozzle actually fails and thus potentially produces waste, but rathertakes preemptive action.

Advantageous and thus preferred further developments of the method willbecome apparent from the associated dependent claims and from thedescription together with the associated drawings.

Another preferred development of the method of the invention in thiscontext is that the printing nozzle test chart is printed in such a waythat it is formed of a specified number of horizontal rows ofequidistant vertical lines that are printed periodically and aredisposed underneath one another, wherein in every row of the nozzle testchart only those printing nozzles of the print head in the ink jetprinting machine that correspond to the specified number of horizontalrows periodically contribute to the first element of the printing nozzletest chart. Many types of printing nozzle test charts are known. Aparticularly suitable type is formed of a specified number of horizontalrows with equidistant lines or stripes printed vertically. Since imagesensors that use current sensor technology have a significantly lowerresolution than the actual print that is produced, not all neighboringprinting nozzles may print directly next to one another because the atleast one image sensor does not have the required resolution todistinguish between these individual lines. Consequently, only everytenth vertical line, for instance, is printed by the correspondingprinting nozzle in a horizontal row. In order to include all printingnozzles and allow them to print their vertical lines, the printingnozzle test chart is formed of a total of ten horizontal rows.

A further preferred development of the method of the invention in thiscontext is that the characteristic values include the thickness, slopeand color value of the vertically printed equidistant lines as well asthe utilized capacity of the contributing nozzles. The correspondingcharacteristic values to be used for assessing the current performanceof the tested printing nozzles are, among others, the thickness, angle,and color value of the vertically printed lines as indicated above.Naturally, these values also apply if other types of printing nozzletest charts are used. In such a case, however, the characteristic valueswould potentially have to be adapted to the different form of theindividual image objects in the form of the vertical lines that areprinted in the test chart by the printing nozzles. An important aspectis that the utilized capacity of the contributing printing nozzles isincluded as a characteristic value because the performance of theindividual printing nozzles is particularly dependent on the utilizedcapacity thereof.

An added preferred development of the method of the invention in thiscontext is that the failure probability of every printing nozzlerepresents the probability of the respective printing nozzle to exceed atolerance for the print quality resulting from the characteristicvalues. While the decision whether a printing nozzle is deactivated andneeds to be compensated for is made by assessing whether the failureprobability exceeds a specified threshold, the failure probabilityitself is defined by assessing whether the performance of a specificprinting nozzle as indicated by the characteristic values exceeds adefined threshold for these characteristic values. Thus, the probabilityfor the current characteristic values of a printing nozzle to exceed thetolerances for these characteristic values is established.

An additional preferred development of the method of the invention inthis context is that to apply the prediction model, the characteristicvalues are established multiple times for every printing nozzle, withevery assessment of a printed printing nozzle test chart correspondingto one pass, and the characteristic values that have been establishedmultiple times in this way are saved and used to calculate the failureprobability. In order to maximize the accuracy of the characteristicvalues and thus to be able to apply the prediction model as accuratelyas possible, it is expedient to establish the characteristic values thatindicate the current state of every single printing nozzle multipletimes. This is done by printing the printing nozzle test chart multipletimes, evaluating it multiple times by using the image recording system,and saving the results for further use when the failure probability iscalculated. In this context it should be noted that determining thecharacteristic values multiple times to describe the current state isexpedient on one hand because averaging the characteristic values thathave been established multiple times may eliminate individualmeasurement errors and on the other hand especially because it allowsthe actual progression of the characteristic values to be visualizedover time. This progression over time is an important criterion to beable to prognosticate the future progression of the characteristicvalues and thus the performance of the printing nozzle.

Another preferred development of the method of the invention in thiscontext is that the characteristic values that have been establishedmultiple times are used as a function of the process variation of thecharacteristic values over their progression in the individual passes,wherein for the same failure probability, progressions with lowerprocess variation of the characteristic values are allowed to get closerto the tolerance limit than progressions with greater process variation.If one considers the progression of the established characteristicvalues over time, the corresponding process variation of thecharacteristic values will have to be factored in. This means thatcharacteristic values that fluctuate considerably, i.e. that vary,contain a much greater uncertainty factor. A reason for such variationmay of course be measurement errors on one hand and a printing nozzlethat is actually highly volatile in terms of its print quality. The keyaspect is that in terms of the further progression of its characteristicvalues that is to be predicted, a printing nozzle having characteristicvalues which fluctuate to a considerable extent has immediateconsequences for the determination of the failure probability. Theprogression of the characteristic values of a printing nozzle thatexhibits only little variation is thus allowed to get much closer to thetolerance limit because statistically one may assume that the futuredevelopment of the characteristic values will be subject to littlevariation and thus the probability of the characteristic valuesexceeding the tolerance is much lower than if the progression of thecharacteristic values varies to a greater extent. Conversely, this meansthat on average, a characteristic value progression that varies to agreat extent must not be allowed to get close to the tolerance limitbecause in such a case the future development must be expected to varygreatly too, resulting in a much greater probability for individualcharacteristic values to exceed the tolerance if the values were allowedto get closer to the tolerance limit. In the end, this means that forthe same resultant failure probability, characteristic valueprogressions of low variation may be allowed to get closer to thetolerance limit than progressions with greater variation.

A further preferred development of the method of the invention in thiscontext is that the characteristic values that have been establishedmultiple times are converted into statistic process factors in the formof an expectation value and a confidence interval and the statisticprocess factors are determined by linear or non-linear regression of thecharacteristic values that have been determined multiple times, with aregression model of any desired order being used for the linear ornon-linear regression. The determined characteristic values thatdescribe the current state of the printing nozzle may be converted intostatistic process factors such as the expectation value and a confidenceinterval. They are determined by linear or non-linear regression of thecharacteristic values. A model of any desired order may be used for theregression. A model of the first order, for instance, means linearregression. A model of zero order means no regression, i.e. thestatistic variables accordingly correspond to the average and standarddeviation of expectation value and confidence interval.

An added preferred development of the method of the invention in thiscontext is that the statistic variables are formed with a time-basedweighting of the characteristic values that have been establishedmultiple times, wherein the time-based weighting occurs in such a waythat newer characteristic values are given linearly or exponentiallymore weight than older characteristic values. Thus, when the statisticprocess factors to be used in a future calculation of the failureprobability are established, a time-based weighting of thecharacteristic values that have been established multiple times is to bemade. This time-based weighting means that newer characteristic valuesare given a greater weight than older characteristic values. If it isapplied, it may be a linear or exponential weighting, which means thatfor a linear weighting, the weight of the core values increases morelinearly the newer they are while for an exponential weighting, thesignificance of the core values increases exponentially.

An additional preferred development of the method of the invention inthis context is that printing nozzles that have been switched off forthe printing of an image continue to contribute to the printing of theprinting nozzle test chart, the failure probability continues to becalculated for these printing nozzles and, when the calculated failureprobability remains below a second defined threshold, these printingnozzles are used again to print the image in the production run. Animportant aspect of the method of the invention is that due to theprediction of the future behavior of the contributing printing nozzles,the printing nozzles are continuously monitored in terms of theircurrent state. This also applies to printing nozzles that exceed afailure probability threshold and are thus deactivated. This means thatthe printing nozzles are only deactivated for the actual print, i.e. theimage to be printed, while they continue to contribute to the printingof the printing nozzle test chart. Thus, they continue to be monitoredin terms of their performance even when they have been switched off forthe print. If their characteristic values and thus their performancechange, for instance if their failure probability sinks below thethreshold due to a lower utilized capacity, these printing nozzles mayagain be used to print the actual print in the production run tocomplete the actual print job. In this context, the failure probabilitythresholds that determine whether a printing nozzle needs to bedeactivated and thus compensated for or whether it may be reactivatedfor the production run are two different parameters. They may have anidentical value though.

A concomitant preferred development of the method of the invention inthis context is that to calculate the failure probability of allprinting nozzles that contribute to the printing of the printing nozzletest charts, multimodal distributions of the characteristic values areassumed and used apart from a unimodal distribution. Apart from thestandard unimodal distribution, the distribution may include bimodaldistributions or multimodal distributions in general. This refers to theprobability distribution of the occurrence of individual characteristicvalues for which one or more statistic modes may correspondingly beassumed, and the corresponding consequences for the evaluation todetermine the failure probability.

The invention as such as well as further developments of the inventionthat are advantageous in structural and/or functional terms will bedescribed in more detail below with reference to the associated drawingsand based on at least one preferred exemplary embodiment.

Other features which are considered as characteristic for the inventionare set forth in the appended claims.

Although the invention is illustrated and described herein as embodiedin a method for detecting and compensating for defective printingnozzles in an ink jet printing machine, it is nevertheless not intendedto be limited to the details shown, since various modifications andstructural changes may be made therein without departing from the spiritof the invention and within the scope and range of equivalents of theclaims.

The construction and method of operation of the invention, however,together with additional objects and advantages thereof will be bestunderstood from the following description of specific embodiments whenread in connection with the accompanying drawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

FIG. 1 is a diagrammatic, longitudinal-sectional view of an example of asheet-fed ink jet printing machine;

FIG. 2 is a fragmentary, top-plan view of an example of a printingnozzle test chart which is used having horizontal rows of equidistantvertical lines;

FIG. 3 is a diagram illustrating two examples of a characteristic valueprogression over time and a corresponding tolerance threshold;

FIG. 4 is a flow chart illustrating the method of the invention;

FIG. 5 is a flow chart illustrating a calculation of a failureprobability; and

FIG. 6 is a flow chart illustrating a prediction model.

DETAILED DESCRIPTION OF THE INVENTION

Referring now in detail to the figures of the drawings, in whichmutually corresponding elements have the same reference symbols, andfirst, particularly, to FIG. 1 thereof, it is seen that the field ofapplication of the preferred exemplary embodiment is an inkjet printingmachine 7. FIG. 1 shows an example of the fundamental construction ofsuch a machine 7, including a feeder 1 for feeding a printing substrate2, a printing unit 4 in which the printing substrate receives an imageprinted by print heads 5 and a delivery 3. The machine 7 is a sheet-fedink jet printing machine 7 controlled by a control unit 6.

A preferred embodiment of the method of the invention is shown in FIG.4. A first step in the processing of the print job is to print a digitalprinting nozzle test chart 16 or several different ones during aproduction run. The test chart 16 is formed of multiple horizontal rowsof vertical lines 11, with every printing nozzle per print head 5printing at least one vertical line 11. Such a printed test chart 17 isshown in FIG. 2, where only every x^(th) printing nozzle creates avertical line 11 in a horizontal row, which means that x horizontal rowsneed to be printed per printing nozzle test chart 17 for every printingnozzle to create at least one vertical line 11. The figure shows theimage objects 11, i.e. the vertical lines 11 that have been printed bydefective printing nozzles, for instance an object 8 printed by failedprinting nozzles, an object 9 printed by printing nozzles that print ina deviating way, and an object 10 printed by printing nozzles that printa reduced amount of ink. Characteristic values 28 in the form of thethickness, slope, and color value of the vertical lines may becalculated from these particular vertical lines. The utilized capacityof the contributing printing nozzles is also included in thecharacteristic values 28. At least one image sensor 29 of an imagerecording system then scans and digitizes the printed test charts 17 andforwards them to the evaluation computer 6. With the aid of theprediction model, the evaluation computer 6 calculates a failureprobability 14 of every single printing nozzle that contributed to theprinted printing nozzle test chart 17. When the failure probability 14of a printing nozzle exceeds a set threshold 18, the printing nozzle 20in question is deactivated and compensated for in the printing of theactual print. Then the actual printing operation to complete the printjob continues. The defective printing nozzles 20 that have been detectedin a corresponding way in the form of a failure probability 14 availablefor every printing nozzle are deactivated as a function of the failureprobability 14 and thus need to be compensated for. At the same time,compensated printing nozzles 20 that are no longer used to print theactual print because their failure probability 14 was too high continueto be used to print the digital printing nozzle test charts 16 and to beevaluated. If they stay below a corresponding second threshold 27 andare thus usable for printing the actual print, they will be switched onagain and no compensation is made.

The calculation of the failure probability 14 is schematically shown inmore detail in FIG. 5. The calculation is formed of calculating thecharacteristic values 28 that describe the performance of the individualprinting nozzles and are obtained from the computer's evaluation of thetest charts 19 that have been printed and recorded multiple times. Anintrinsic aspect of the method is that characteristic values 28 aretreated in accordance with their process variation 23. This means thatfor the same failure probability 14, progressions with a low variation23 are allowed to get closer to a tolerance threshold 26 thanprogressions with greater variation 23. FIG. 3 shows this by way ofexample for two progressions of characteristic values 28, one with lowvariation 12, which is allowed to get closer to the tolerance threshold,and one with greater variation 13, which is not. The x-axis of FIG. 3shows the number of measurements 15 taken to calculate thecharacteristic values, while the y-axis indicates the failureprobability 14. Both characteristic value progressions 12, 13 have anormal distribution and have the same failure probability 14 in terms ofthe tolerance threshold 26. If this failure probability 14 was justabout to exceed the acceptable tolerance threshold 26, both printingnozzles would be switched off even though for the progression that hasthe wide variation 23, a failure is not yet evident. In a further step,factoring in the variation 23 of characteristic values 24 by using aregression involving a time-based weighting, statistic process factors21, 22 for determining the failure probability 14 are calculated in theform of an expectation value 21 and a confidence interval 22. In orderto calculate the process factors 21, 22 by regression, a progressionover time of the individual characteristic values 25 is factored in inthe weighting. These process factors 21, 22 are then used to calculatethe failure probability 14 by comparing the characteristic valueprogression to the tolerance threshold 26. The failure probability value14 is determined by the probability of whether the future progression ofthe characteristic values 24, 25 that may be derived from the processfactors 21, 22 will exceed the tolerance limit 26.

The prediction model that is applied itself will be explained in moredetail with reference to FIG. 6. The model is based on the known priorart process of establishing suitable characteristic values 28 for everyprinting nozzle in an ongoing print run. This means that for everyprinting nozzle, the last n (e.g. five) measured values are saved andprocessed. The characteristic values 28 of the printing nozzles follow astatistic distribution, ideally a normal distribution. Based on theassumption that the characteristic values are normally distributed, theprobability 14 of the print quality tolerance threshold 26 to beexceeded may be calculated in a statistic calculation. It is no longerpurely measured values that are used but statistic process factors 21,22, preferably expectation value 21 and confidence interval 22. Thus,for every printing nozzle, there is an expectation value 21 and aconfidence interval 22, which allow the failure probability 14 of everyprinting nozzle to be determined. When a specific threshold p₀ 18 suchas 1% failure probability 14 is exceeded, the printing nozzle 20 isswitched off. It is likewise possible to switch a switched-off nozzle 20back on when its failure probability 14 drops below a specific thresholdp₁ 27 such as 1% failure probability 14. The two thresholds p₀ 18 and p₁27 may or may not have the same value. In this context, p₀ will alwaysbe less than or equal to p1.

The statistic process factors 21, 22 are calculated by regression, e.g.linear or non-linear regression, from the time series of n values. Ifn=1, the method becomes the known prior art method. The regression modelthat is used may be of any desired (i.e. n^(th)) order. Typically,however, it will be of 1^(st) order for a linear regression. For aregression model of zero order, there is no regression, the statisticprocess factors of expectation value 21 and confidence interval 22correspond to the average and the standard deviation.

The statistic process factors 21, 22 may be created with or without atime-based weighting of the values of the n measurements. In thiscontext, any desired time-based weighting may be applied. If it isapplied, newer data will typically have a higher weighting than olderdata, namely in the form of a linear or exponential weighting.

A further preferred embodiment of the prediction model may be createdwhen the behavior of the n measured values over time is factored in. Inthis case, based on the regression, an extrapolation is made for thenext expectation value 21 and the corresponding confidence interval 22.

A typical implementation appears as follows:

Number of measured values, n: 1 to 100, typically 10.

Threshold p0: 0.01% to 50% failure probability, typically 1%.

Threshold p1: 0.01% to 50% failure probability, typically 1%.

In a nutshell, this means that based on a time series analysis of thevalues of the characteristics of the printing nozzles and theinference-statistic analysis thereof with closing statistics, the futuredevelopment of the performance of the printing nozzles including theassociated failure probabilities 14 in the form ofuncertainties/confidence intervals may be predicted in accordance withthe aid of the prediction model in accordance with the method of theinvention. This is a way to make a decision whether a printing nozzle isto be switched on or whether it is to be switched off and compensatedfor before it may produce waste in the form of unacceptable prints.

A further preferred embodiment of the method of the invention relates tothe statistic evaluation of the measured data. Apart from a unimodaldistribution of the characteristic values 28 of a printing nozzle, amultimodal distribution may be assumed. When a unimodal distribution isassumed in the specific case of a normal distribution, thecharacteristic values 28 of the printing nozzles may be described withsufficient accuracy.

When a multimodal distribution is assumed, the following applies: Sinceonly a very limited number of measured values is available, it isnecessary to estimate the distribution function from which the failureprobabilities 14 may then be differentiated. If the distributionfunction is known, the failure probability 14 may be determined bynumerical integration of the distribution function. One possible way ofestimating the density function is to use a so-called kernel densityestimation.

In the embodiment described above involving unimodal distribution, thestatistics of the individual nozzle is described, for instance, by anaverage and the standard deviation when a normal distribution isassumed. The failure probability 14 is then calculated therefrom. At anormal distribution, a value that has a failure probability 14 of 1%,for instance, corresponds to the average or expectation value 21multiplied by the 2,576-fold of the standard deviation. In the case ofregression, this works in an analogous way for the confidence interval22.

For a multimodal distribution, the determination of the failureprobability 14 is done purely numerically. Initially, the distributionfunction is estimated in a numeric process and subsequently, the failureprobability 14 is obtained by a numeric integration of the distributionfunction.

The following is a summary list of reference numerals and thecorresponding structure used in the above description of the invention:

1 feeder

2 printing substrate

3 delivery

4 ink jet printing unit

5 ink jet print head

6 computer

7 ink jet printing machine

8 failed printing nozzle

9 printing nozzle that prints incorrectly

10 printing nozzle that prints a reduced amount

11 printing nozzle image object

12 characteristic value progression with little variation

13 characteristic value progression with great variation

14 failure probability

15 number of measuring processes for characteristic value calculation

16 digital test chart

17 printed test chart

18 threshold for switching off a printing nozzle

19 printed and recorded test chart

20 printing nozzles that have been switched off and compensated for

21 statistic process factor of expectation value

22 statistic process factor of confidence interval

23 characteristic value variation

24 characteristic values factoring in variation

25 characteristic values factoring in regression and variation

26 tolerance limit for characteristic values

27 threshold for switching a printing nozzle on again

28 characteristic values

The invention claimed is:
 1. A method for detecting and compensating forfailed printing nozzles in an ink jet printing machine by using acomputer, the method comprising the following steps: carrying outprinting of printing nozzle test charts next to an actual print during aproduction run and subsequently recording and digitizing the printedprinting nozzle test charts by using at least one image sensor;evaluating the recorded test charts and, based thereon, determiningcharacteristic values for all printing nozzles contributing to theprinting of the printing nozzle test chart by using the computer;calculating a failure probability for every contributing printing nozzlebased on the determined characteristic values by applying a statisticalprediction model by using the computer; for the application of theprediction model, establishing the characteristic values for everyprinting nozzle multiple times, with every evaluation of the printedprinting nozzle test chart corresponding to one pass, and saving andusing the characteristic values having been established multiple timesto calculate the failure probability; switching off all printing nozzlesexceeding a first defined threshold for the calculated failureprobability and compensating for the switched-off nozzles; and carryingout a printing operation on the ink jet printing machine with printingnozzle compensation.
 2. The method according to claim 1, which furthercomprises printing the printing nozzle test chart by forming a specifiednumber of horizontal rows of equidistant vertical lines printedperiodically and disposed underneath one another, and providing everyrow of the nozzle test chart with only those printing nozzles of theprint head of the ink jet printing machine corresponding to thespecified number of the horizontal rows periodically contributing to afirst element of the printing nozzle test chart.
 3. The method accordingto claim 2, which further comprises including thickness, slope and colorvalue of the vertically printed equidistant lines as well as a utilizedcapacity of the contributing printing nozzles in the characteristicvalues.
 4. The method according to claim 1, which further comprisesusing the failure probability of every one of the printing nozzles torepresent a probability that a printing nozzle will exceed a tolerancelimit for print quality resulting from the characteristic values.
 5. Themethod according to claim 1, which further comprises using thecharacteristic values having been established multiple times as afunction of a process variation of the characteristic values over aprogression of individual passes, and for the same failure probability,allowing the characteristic values of progressions of lower processvariation of the characteristic values to get closer to a tolerancelimit than progressions of greater process variation.
 6. The methodaccording to claim 5, which further comprises converting thecharacteristic values having been established multiple times intostatistical process factors forming an expectation value and aconfidence interval, determining the statistical process factors bylinear or non-linear regression of the characteristic values having beenestablished multiple times, and using a regression model of any desiredorder for the linear or non-linear regression.
 7. The method accordingto claim 6, which further comprises creating the statistical processfactors with a time-based weighting of the characteristic values havingbeen established multiple times, and carrying out the time-basedweighting by causing newer characteristic values to have a linearly orexponentially higher weight than older characteristic values.
 8. Themethod according to claim 1, which further comprises calculating thefailure probability for all printing nozzles contributing to theprinting of the printing nozzle test charts by assuming and usingmultimodal distributions of the characteristic values in addition to aunimodal distribution of the characteristic values.
 9. A method fordetecting and compensating for failed printing nozzles in an ink jetprinting machine by using a computer, the method comprising thefollowing steps: carrying out printing of printing nozzle test chartsnext to an actual print during a production run and subsequentlyrecording and digitizing the printed printing nozzle test charts byusing at least one image sensor; evaluating the recorded test chartsand, based thereon, determining characteristic values for all printingnozzles contributing to the printing of the printing nozzle test chartby using the computer; calculating a failure probability for everycontributing printing nozzle based on the determined characteristicvalues by applying a statistical prediction model by using the computer;switching off all printing nozzles exceeding a first defined thresholdfor the calculated failure probability and compensating for theswitched-off nozzles; allowing printing nozzles having been switched offfor the printing of the actual print to still contribute to the printingof the printing nozzle test charts; continuing to calculate a failureprobability for the switched off printing nozzles; again using theswitched off printing nozzles for printing the actual print in theproduction run if the calculated failure probability stays below asecond defined threshold; and carrying out a printing operation on theink jet printing machine with printing nozzle compensation.